Generally, question answering is a type of information retrieval. Given a collection of documents (such as on the World Wide Web or a local database) the system should be able to retrieve and/or construct answers to questions using natural language processing techniques that are typically more complex than for other types of information retrieval. Understanding the specific user query and finding the appropriate documents that might contain the answer to the user query can be challenging.
Question answering research attempts to deal with a wide range of question types including: fact, list, definition, how, why, hypothetical, semantically-constrained, and cross-lingual questions, among others. Search collections vary from small local document collections, to internal organization documents, to compiled newswire reports, to much larger and more comprehensive corpuses such as the World Wide Web.